high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

GPTPU: Accelerating Applications using Edge Tensor Processing Units

Kuan-Chieh Hsu, Hung-Wei Tseng

View

Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Machine learning, Neural networks, nVidia, OpenCL, TPU

July 18, 2021 by hgpu

Bringing OpenCL to Commodity RISC-V CPUs

Tine Blaise, Seyong Lee, Jeff Vetter, Hyesoon Kim

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, HPC, OpenCL, Package

July 11, 2021 by hgpu

Block Conjugate Gradient Solver in OpenCL

Kert Tali, Eero Vainikko

View

Download (PDF)

Tags: Algorithms, Computer science, Conjugate gradient solver, Linear Algebra, nVidia, nVidia GeForce RTX 2080, OpenCL

July 11, 2021 by hgpu

KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks

J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian Foster, Zhao Zhang

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia A100, nVidia DGX-A100, Package, Tesla V100

July 11, 2021 by hgpu

Dynamic Adaptation Techniques and Opportunities to Improve HPC Runtimes

Mohammad Alaul Haque Monil

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL

July 11, 2021 by hgpu

Opening the Black Box: Performance Estimation during Code Generation for GPUs

Dominik Ernst, Georg Hager, Markus Holzer, Matthias Knorr, Gerhard Wellein

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, Lattice Boltzmann model, Machine learning, nVidia, Performance, Stencil computation, Tesla V100

July 11, 2021 by hgpu

A Sorting Library for FPGA Implementation in OpenCL Programming

Ryohei Kobayashi, Kento Miura, Norihisa Fujita, Taisuke Boku, Toshiyuki Amagasa

View

Download (PDF)

Tags: Algorithms, Computer science, FPGA, nVidia, OpenCL, Sorting, Tesla V100

July 4, 2021 by hgpu

Optimization of Heterogeneous Parallel Computing Systems using Machine Learning

Devi Abhiseshu Adurti, Mohit Battu

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, Matrix multiplication, nVidia, nVidia GeForce GTX 1050 Ti, Thesis

July 4, 2021 by hgpu

Sigmoid: An auto-tuned load balancing algorithm for heterogeneous systems

Borja Pérez, E. Stafford, J.L. Bosque, R. Beivide

View

Download (PDF)

Tags: Algorithms, Computer science, Heterogeneous systems, load balancing, nVidia, nVidia GeForce GTX Titan Black, OpenCL, Tesla K20

June 27, 2021 by hgpu

Improving Performance and Energy Efficiency of Heterogeneous Systems with rCUDA

Javier Prades Gasulla

View

Download (PDF)

Tags: Cloud, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20, Tesla K40, Tesla P100, Thesis, Virtualization

June 27, 2021 by hgpu

Efficient heterogeneous matrix profile on a CPU + High Performance FPGA with integrated HBM

Jose Carlos Romero, Angeles Navarro, Antonio Vilches, Andrés Rodríguez, Francisco Corbera, Rafael Asenjo

View

Download (PDF)

Tags: Algorithms, Analytical model, Computer science, FPGA, Heterogeneous systems, OpenCL

June 27, 2021 by hgpu

APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores

Boyuan Feng, Yuke Wang, Tong Geng, Ang Li, Yufei Ding

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce RTX 3090, Package, Precision, Python, Tesla A100

June 27, 2021 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Programming

GPTPU: Accelerating Applications using Edge Tensor Processing Units

Bringing OpenCL to Commodity RISC-V CPUs

Block Conjugate Gradient Solver in OpenCL

KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks

Dynamic Adaptation Techniques and Opportunities to Improve HPC Runtimes

Opening the Black Box: Performance Estimation during Code Generation for GPUs

A Sorting Library for FPGA Implementation in OpenCL Programming

Optimization of Heterogeneous Parallel Computing Systems using Machine Learning

Sigmoid: An auto-tuned load balancing algorithm for heterogeneous systems

Efficient heterogeneous matrix profile on a CPU + High Performance FPGA with integrated HBM

APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Most viewed papers (last 30 days)